Overview

Brought to you by YData

Dataset statistics

Number of variables39
Number of observations8878
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory138.0 B

Variable types

Numeric11
Categorical2
Boolean26

Alerts

estado_civil_CASADO is highly overall correlated with estado_civil_SOLTEROHigh correlation
estado_civil_SOLTERO is highly overall correlated with estado_civil_CASADOHigh correlation
estado_cliente_ACTIVO is highly overall correlated with estado_cliente_PASIVO and 2 other fieldsHigh correlation
estado_cliente_PASIVO is highly overall correlated with estado_cliente_ACTIVO and 2 other fieldsHigh correlation
falta_pago_N is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
falta_pago_Y is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
gastos_ult_12m is highly overall correlated with operaciones_ult_12mHigh correlation
genero_F is highly overall correlated with genero_MHigh correlation
genero_M is highly overall correlated with genero_FHigh correlation
importe_solicitado is highly overall correlated with pct_ingresoHigh correlation
operaciones_ult_12m is highly overall correlated with gastos_ult_12mHigh correlation
pct_ingreso is highly overall correlated with importe_solicitadoHigh correlation
situacion_vivienda_ALQUILER is highly overall correlated with situacion_vivienda_HIPOTECAHigh correlation
situacion_vivienda_HIPOTECA is highly overall correlated with situacion_vivienda_ALQUILERHigh correlation
tasa_interes is highly overall correlated with falta_pago_N and 1 other fieldsHigh correlation
situacion_vivienda_OTROS is highly imbalanced (96.3%) Imbalance
situacion_vivienda_PROPIA is highly imbalanced (63.8%) Imbalance
objetivo_credito_MEJORAS_HOGAR is highly imbalanced (57.5%) Imbalance
estado_civil_DESCONOCIDO is highly imbalanced (62.1%) Imbalance
estado_civil_DIVORCIADO is highly imbalanced (61.7%) Imbalance
nivel_educativo_POSGRADO_COMPLETO is highly imbalanced (72.9%) Imbalance
nivel_educativo_POSGRADO_INCOMPLETO is highly imbalanced (70.5%) Imbalance
antiguedad_empleado has 1276 (14.4%) zeros Zeros
personas_a_cargo has 787 (8.9%) zeros Zeros

Reproduction

Analysis started2025-05-06 17:21:29.701783
Analysis finished2025-05-06 17:21:55.392433
Duration25.69 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

edad
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.540324
Minimum20
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:55.509939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21
Q122
median23
Q325
95-th percentile26
Maximum26
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5114398
Coefficient of variation (CV)0.064206412
Kurtosis-1.0416921
Mean23.540324
Median Absolute Deviation (MAD)1
Skewness0.10738576
Sum208991
Variance2.2844501
MonotonicityNot monotonic
2025-05-06T19:21:55.609277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
22 1935
21.8%
23 1924
21.7%
24 1695
19.1%
25 1444
16.3%
26 1183
13.3%
21 691
 
7.8%
20 6
 
0.1%
ValueCountFrequency (%)
20 6
 
0.1%
21 691
 
7.8%
22 1935
21.8%
23 1924
21.7%
24 1695
19.1%
25 1444
16.3%
26 1183
13.3%
ValueCountFrequency (%)
26 1183
13.3%
25 1444
16.3%
24 1695
19.1%
23 1924
21.7%
22 1935
21.8%
21 691
 
7.8%
20 6
 
0.1%

importe_solicitado
Real number (ℝ)

High correlation 

Distinct485
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8164.6063
Minimum500
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:55.718251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2000
Q14500
median6500
Q310000
95-th percentile20000
Maximum35000
Range34500
Interquartile range (IQR)5500

Descriptive statistics

Standard deviation5745.9152
Coefficient of variation (CV)0.70375901
Kurtosis2.3379036
Mean8164.6063
Median Absolute Deviation (MAD)2500
Skewness1.5236951
Sum72485375
Variance33015542
MonotonicityNot monotonic
2025-05-06T19:21:55.886023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 693
 
7.8%
6000 641
 
7.2%
8000 499
 
5.6%
7000 390
 
4.4%
4000 386
 
4.3%
10000 333
 
3.8%
3000 325
 
3.7%
20000 251
 
2.8%
12000 228
 
2.6%
9000 221
 
2.5%
Other values (475) 4911
55.3%
ValueCountFrequency (%)
500 3
 
< 0.1%
700 1
 
< 0.1%
750 1
 
< 0.1%
800 1
 
< 0.1%
900 1
 
< 0.1%
1000 122
1.4%
1050 1
 
< 0.1%
1100 1
 
< 0.1%
1150 1
 
< 0.1%
1200 60
0.7%
ValueCountFrequency (%)
35000 19
0.2%
34800 1
 
< 0.1%
34000 1
 
< 0.1%
33950 1
 
< 0.1%
33000 1
 
< 0.1%
32500 1
 
< 0.1%
32000 1
 
< 0.1%
31300 1
 
< 0.1%
31050 1
 
< 0.1%
30000 18
0.2%

duracion_credito
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.7 KiB
2
2991 
3
2944 
4
2943 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8878
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row4
4th row2
5th row3

Common Values

ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

Length

2025-05-06T19:21:56.044979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-06T19:21:56.186868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

Most occurring characters

ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2991
33.7%
3 2944
33.2%
4 2943
33.1%

antiguedad_empleado
Real number (ℝ)

Zeros 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9047083
Minimum0
Maximum11
Zeros1276
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:56.337674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile9
Maximum11
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8431527
Coefficient of variation (CV)0.72813448
Kurtosis-0.90312648
Mean3.9047083
Median Absolute Deviation (MAD)2
Skewness0.32364042
Sum34666
Variance8.0835173
MonotonicityNot monotonic
2025-05-06T19:21:56.886038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 1276
14.4%
2 1158
13.0%
3 1038
11.7%
5 967
10.9%
6 921
10.4%
1 908
10.2%
4 770
8.7%
7 706
8.0%
8 525
5.9%
9 368
 
4.1%
Other values (2) 241
 
2.7%
ValueCountFrequency (%)
0 1276
14.4%
1 908
10.2%
2 1158
13.0%
3 1038
11.7%
4 770
8.7%
5 967
10.9%
6 921
10.4%
7 706
8.0%
8 525
5.9%
9 368
 
4.1%
ValueCountFrequency (%)
11 23
 
0.3%
10 218
 
2.5%
9 368
 
4.1%
8 525
5.9%
7 706
8.0%
6 921
10.4%
5 967
10.9%
4 770
8.7%
3 1038
11.7%
2 1158
13.0%

ingresos
Real number (ℝ)

Distinct1619
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50918.641
Minimum9600
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:57.111299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9600
5-th percentile21000
Q134000
median47000
Q360000
95-th percentile97000
Maximum500000
Range490400
Interquartile range (IQR)26000

Descriptive statistics

Standard deviation28814.656
Coefficient of variation (CV)0.56589601
Kurtosis21.101477
Mean50918.641
Median Absolute Deviation (MAD)13000
Skewness3.3480253
Sum4.520557 × 108
Variance8.3028441 × 108
MonotonicityNot monotonic
2025-05-06T19:21:57.373930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 386
 
4.3%
30000 313
 
3.5%
50000 304
 
3.4%
40000 242
 
2.7%
45000 217
 
2.4%
55000 201
 
2.3%
65000 197
 
2.2%
48000 193
 
2.2%
36000 185
 
2.1%
42000 176
 
2.0%
Other values (1609) 6464
72.8%
ValueCountFrequency (%)
9600 3
 
< 0.1%
9840 1
 
< 0.1%
9900 1
 
< 0.1%
9960 1
 
< 0.1%
10000 9
0.1%
10560 1
 
< 0.1%
10668 1
 
< 0.1%
10800 3
 
< 0.1%
10980 1
 
< 0.1%
11000 3
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
306000 1
 
< 0.1%
300000 6
0.1%
287000 1
 
< 0.1%
280000 1
 
< 0.1%
277104 1
 
< 0.1%
275000 1
 
< 0.1%
260000 1
 
< 0.1%
259000 1
 
< 0.1%
255000 1
 
< 0.1%

pct_ingreso
Real number (ℝ)

High correlation 

Distinct67
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17502929
Minimum0.01
Maximum0.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:57.589710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.09
median0.15
Q30.23
95-th percentile0.39
Maximum0.71
Range0.7
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.10740906
Coefficient of variation (CV)0.61366337
Kurtosis0.9673682
Mean0.17502929
Median Absolute Deviation (MAD)0.07
Skewness1.0299963
Sum1553.91
Variance0.011536706
MonotonicityNot monotonic
2025-05-06T19:21:57.717174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 463
 
5.2%
0.13 406
 
4.6%
0.09 391
 
4.4%
0.11 387
 
4.4%
0.08 386
 
4.3%
0.15 380
 
4.3%
0.12 352
 
4.0%
0.14 348
 
3.9%
0.07 346
 
3.9%
0.17 335
 
3.8%
Other values (57) 5084
57.3%
ValueCountFrequency (%)
0.01 17
 
0.2%
0.02 81
 
0.9%
0.03 198
2.2%
0.04 249
2.8%
0.05 262
3.0%
0.06 304
3.4%
0.07 346
3.9%
0.08 386
4.3%
0.09 391
4.4%
0.1 463
5.2%
ValueCountFrequency (%)
0.71 1
 
< 0.1%
0.69 2
 
< 0.1%
0.67 1
 
< 0.1%
0.65 2
 
< 0.1%
0.64 3
< 0.1%
0.63 1
 
< 0.1%
0.61 1
 
< 0.1%
0.6 2
 
< 0.1%
0.59 5
0.1%
0.58 1
 
< 0.1%

tasa_interes
Real number (ℝ)

High correlation 

Distinct306
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.017654
Minimum5.42
Maximum22.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:57.833661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile6.03
Q17.9
median10.99
Q313.47
95-th percentile16.29
Maximum22.11
Range16.69
Interquartile range (IQR)5.57

Descriptive statistics

Standard deviation3.1940462
Coefficient of variation (CV)0.28990258
Kurtosis-0.70362983
Mean11.017654
Median Absolute Deviation (MAD)2.5
Skewness0.18457975
Sum97814.73
Variance10.201931
MonotonicityNot monotonic
2025-05-06T19:21:57.964780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.99 252
 
2.8%
7.51 227
 
2.6%
7.9 189
 
2.1%
7.49 187
 
2.1%
7.88 173
 
1.9%
5.42 171
 
1.9%
9.99 148
 
1.7%
11.49 143
 
1.6%
11.71 132
 
1.5%
13.49 132
 
1.5%
Other values (296) 7124
80.2%
ValueCountFrequency (%)
5.42 171
1.9%
5.79 106
1.2%
5.99 112
1.3%
6 6
 
0.1%
6.03 121
1.4%
6.17 59
 
0.7%
6.39 14
 
0.2%
6.54 71
0.8%
6.62 116
1.3%
6.76 61
 
0.7%
ValueCountFrequency (%)
22.11 1
< 0.1%
21.74 2
< 0.1%
21.36 1
< 0.1%
21.27 1
< 0.1%
21.21 1
< 0.1%
20.89 2
< 0.1%
20.62 1
< 0.1%
20.3 2
< 0.1%
20.25 1
< 0.1%
20.2 1
< 0.1%

estado_credito
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.7 KiB
0
6713 
1
2165 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8878
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

Length

2025-05-06T19:21:58.074280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-06T19:21:58.121201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

Most occurring characters

ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8878
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6713
75.6%
1 2165
 
24.4%

antiguedad_cliente
Real number (ℝ)

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.885898
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:58.211851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q131
median36
Q340
95-th percentile50
Maximum56
Range43
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.994925
Coefficient of variation (CV)0.22278738
Kurtosis0.41237601
Mean35.885898
Median Absolute Deviation (MAD)4
Skewness-0.10240788
Sum318595
Variance63.918826
MonotonicityNot monotonic
2025-05-06T19:21:58.336792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 2123
23.9%
37 316
 
3.6%
34 313
 
3.5%
38 305
 
3.4%
40 303
 
3.4%
39 302
 
3.4%
31 296
 
3.3%
33 278
 
3.1%
35 272
 
3.1%
30 262
 
3.0%
Other values (34) 4108
46.3%
ValueCountFrequency (%)
13 63
0.7%
14 15
 
0.2%
15 29
 
0.3%
16 28
 
0.3%
17 35
 
0.4%
18 49
0.6%
19 55
0.6%
20 68
0.8%
21 75
0.8%
22 93
1.0%
ValueCountFrequency (%)
56 94
1.1%
55 36
 
0.4%
54 47
 
0.5%
53 65
0.7%
52 56
 
0.6%
51 69
0.8%
50 83
0.9%
49 127
1.4%
48 136
1.5%
47 145
1.6%

gastos_ult_12m
Real number (ℝ)

High correlation 

Distinct4718
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4430.9092
Minimum510
Maximum18484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:58.452535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile1289.85
Q12165.5
median3913
Q34748
95-th percentile14230.75
Maximum18484
Range17974
Interquartile range (IQR)2582.5

Descriptive statistics

Standard deviation3426.8069
Coefficient of variation (CV)0.77338684
Kurtosis3.8056338
Mean4430.9092
Median Absolute Deviation (MAD)1312.5
Skewness2.0299172
Sum39337612
Variance11743005
MonotonicityNot monotonic
2025-05-06T19:21:58.578457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4253 10
 
0.1%
4509 10
 
0.1%
4518 9
 
0.1%
2229 9
 
0.1%
4077 8
 
0.1%
4313 8
 
0.1%
4317 8
 
0.1%
4348 8
 
0.1%
4042 8
 
0.1%
1731 8
 
0.1%
Other values (4708) 8792
99.0%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
563 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
644 1
< 0.1%
ValueCountFrequency (%)
18484 1
< 0.1%
17995 1
< 0.1%
17744 1
< 0.1%
17634 1
< 0.1%
17628 1
< 0.1%
17498 1
< 0.1%
17437 1
< 0.1%
17390 1
< 0.1%
17350 1
< 0.1%
17258 1
< 0.1%

limite_credito_tc
Real number (ℝ)

Distinct5667
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8608.6848
Minimum1438.3
Maximum34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:58.698478image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12547.25
median4542.5
Q311054.75
95-th percentile34516
Maximum34516
Range33077.7
Interquartile range (IQR)8507.5

Descriptive statistics

Standard deviation9067.7094
Coefficient of variation (CV)1.0533211
Kurtosis1.8413381
Mean8608.6848
Median Absolute Deviation (MAD)2598
Skewness1.6725368
Sum76427904
Variance82223354
MonotonicityNot monotonic
2025-05-06T19:21:58.815835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 453
 
5.1%
34516 449
 
5.1%
15987 18
 
0.2%
9959 14
 
0.2%
23981 11
 
0.1%
6224 11
 
0.1%
2490 10
 
0.1%
3735 10
 
0.1%
7469 9
 
0.1%
2001 7
 
0.1%
Other values (5657) 7886
88.8%
ValueCountFrequency (%)
1438.3 453
5.1%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
< 0.1%
1446 1
 
< 0.1%
1449 2
 
< 0.1%
1451 2
 
< 0.1%
1452 2
 
< 0.1%
ValueCountFrequency (%)
34516 449
5.1%
34496 1
 
< 0.1%
34458 1
 
< 0.1%
34427 1
 
< 0.1%
34198 1
 
< 0.1%
34173 1
 
< 0.1%
34162 1
 
< 0.1%
34140 1
 
< 0.1%
34058 1
 
< 0.1%
33996 1
 
< 0.1%

operaciones_ult_12m
Real number (ℝ)

High correlation 

Distinct125
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.018135
Minimum10
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:58.950980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile28
Q145
median67
Q381
95-th percentile106
Maximum139
Range129
Interquartile range (IQR)36

Descriptive statistics

Standard deviation23.517037
Coefficient of variation (CV)0.36169966
Kurtosis-0.35631932
Mean65.018135
Median Absolute Deviation (MAD)17
Skewness0.15285337
Sum577231
Variance553.05104
MonotonicityNot monotonic
2025-05-06T19:21:59.175065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69 185
 
2.1%
81 181
 
2.0%
71 180
 
2.0%
75 179
 
2.0%
76 173
 
1.9%
78 173
 
1.9%
82 172
 
1.9%
77 172
 
1.9%
70 166
 
1.9%
67 162
 
1.8%
Other values (115) 7135
80.4%
ValueCountFrequency (%)
10 3
 
< 0.1%
11 2
 
< 0.1%
12 4
 
< 0.1%
13 5
 
0.1%
14 8
 
0.1%
15 12
0.1%
16 12
0.1%
17 12
0.1%
18 21
0.2%
19 10
0.1%
ValueCountFrequency (%)
139 1
 
< 0.1%
138 1
 
< 0.1%
134 1
 
< 0.1%
131 6
0.1%
130 5
0.1%
129 5
0.1%
128 9
0.1%
127 10
0.1%
126 10
0.1%
125 12
0.1%

personas_a_cargo
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3518811
Minimum0
Maximum5
Zeros787
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size138.7 KiB
2025-05-06T19:21:59.375653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3008054
Coefficient of variation (CV)0.55309147
Kurtosis-0.68924218
Mean2.3518811
Median Absolute Deviation (MAD)1
Skewness-0.022285478
Sum20880
Variance1.6920946
MonotonicityNot monotonic
2025-05-06T19:21:59.522758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2388
26.9%
2 2318
26.1%
1 1612
18.2%
4 1397
15.7%
0 787
 
8.9%
5 376
 
4.2%
ValueCountFrequency (%)
0 787
 
8.9%
1 1612
18.2%
2 2318
26.1%
3 2388
26.9%
4 1397
15.7%
5 376
 
4.2%
ValueCountFrequency (%)
5 376
 
4.2%
4 1397
15.7%
3 2388
26.9%
2 2318
26.1%
1 1612
18.2%
0 787
 
8.9%

situacion_vivienda_ALQUILER
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
True
5428 
False
3450 
ValueCountFrequency (%)
True 5428
61.1%
False 3450
38.9%
2025-05-06T19:21:59.638351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_HIPOTECA
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
6076 
True
2802 
ValueCountFrequency (%)
False 6076
68.4%
True 2802
31.6%
2025-05-06T19:21:59.740265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_OTROS
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8843 
True
 
35
ValueCountFrequency (%)
False 8843
99.6%
True 35
 
0.4%
2025-05-06T19:21:59.851740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_PROPIA
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8265 
True
 
613
ValueCountFrequency (%)
False 8265
93.1%
True 613
 
6.9%
2025-05-06T19:21:59.943650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
6816 
True
2062 
ValueCountFrequency (%)
False 6816
76.8%
True 2062
 
23.2%
2025-05-06T19:22:00.032582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7360 
True
1518 
ValueCountFrequency (%)
False 7360
82.9%
True 1518
 
17.1%
2025-05-06T19:22:00.132246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8110 
True
 
768
ValueCountFrequency (%)
False 8110
91.3%
True 768
 
8.7%
2025-05-06T19:22:00.236761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7416 
True
1462 
ValueCountFrequency (%)
False 7416
83.5%
True 1462
 
16.5%
2025-05-06T19:22:00.328806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7423 
True
1455 
ValueCountFrequency (%)
False 7423
83.6%
True 1455
 
16.4%
2025-05-06T19:22:00.418630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7265 
True
1613 
ValueCountFrequency (%)
False 7265
81.8%
True 1613
 
18.2%
2025-05-06T19:22:00.504065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_N
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
True
7315 
False
1563 
ValueCountFrequency (%)
True 7315
82.4%
False 1563
 
17.6%
2025-05-06T19:22:00.605982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_Y
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7315 
True
1563 
ValueCountFrequency (%)
False 7315
82.4%
True 1563
 
17.6%
2025-05-06T19:22:00.679516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_CASADO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
4781 
True
4097 
ValueCountFrequency (%)
False 4781
53.9%
True 4097
46.1%
2025-05-06T19:22:00.730283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DESCONOCIDO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8226 
True
 
652
ValueCountFrequency (%)
False 8226
92.7%
True 652
 
7.3%
2025-05-06T19:22:00.769361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DIVORCIADO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8215 
True
 
663
ValueCountFrequency (%)
False 8215
92.5%
True 663
 
7.5%
2025-05-06T19:22:00.815891image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_SOLTERO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
5412 
True
3466 
ValueCountFrequency (%)
False 5412
61.0%
True 3466
39.0%
2025-05-06T19:22:00.852619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_ACTIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
True
7434 
False
1444 
ValueCountFrequency (%)
True 7434
83.7%
False 1444
 
16.3%
2025-05-06T19:22:00.896172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_PASIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7434 
True
1444 
ValueCountFrequency (%)
False 7434
83.7%
True 1444
 
16.3%
2025-05-06T19:22:00.932315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_F
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
True
4717 
False
4161 
ValueCountFrequency (%)
True 4717
53.1%
False 4161
46.9%
2025-05-06T19:22:00.978270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_M
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
4717 
True
4161 
ValueCountFrequency (%)
False 4717
53.1%
True 4161
46.9%
2025-05-06T19:22:01.027546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7564 
True
1314 
ValueCountFrequency (%)
False 7564
85.2%
True 1314
 
14.8%
2025-05-06T19:22:01.086303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8466 
True
 
412
ValueCountFrequency (%)
False 8466
95.4%
True 412
 
4.6%
2025-05-06T19:22:01.133616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
8417 
True
 
461
ValueCountFrequency (%)
False 8417
94.8%
True 461
 
5.2%
2025-05-06T19:22:01.180618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
7117 
True
1761 
ValueCountFrequency (%)
False 7117
80.2%
True 1761
 
19.8%
2025-05-06T19:22:01.226185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
6139 
True
2739 
ValueCountFrequency (%)
False 6139
69.1%
True 2739
30.9%
2025-05-06T19:22:01.270114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.0 KiB
False
6687 
True
2191 
ValueCountFrequency (%)
False 6687
75.3%
True 2191
 
24.7%
2025-05-06T19:22:01.313150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-05-06T19:21:52.550294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:34.728186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.035753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.518972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:39.753817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.194418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.690079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.484244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:46.660982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.139165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.319433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.651188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:34.892424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.142331image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.676630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.081090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.302168image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.826617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.603499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:46.808677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.272760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.418233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.766477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.017234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.257226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.894837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.186296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.496389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.986899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.722677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:46.951935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.421219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.569155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.881726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.126660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.359695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:38.089994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.290490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.653617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:43.124695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.833842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:47.323958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.531077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.683904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:53.068065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.260978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.553873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:38.385489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.404254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.802414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:43.275295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.949402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:47.427838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.687114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.786973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:53.274234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.390789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.722221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:38.655824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.502627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.933110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:43.445562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:45.052114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:47.611129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:49.900367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.890629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:53.480368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.520696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:36.863046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:38.944811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.603404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.072760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:43.588639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:45.371946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:48.085907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:50.176822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.000252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:53.665999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.606707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.003530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:39.135993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.713862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.207235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:43.931419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:45.608231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:48.439575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:50.402600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.117663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:53.866945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.721802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.129579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:39.381958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.841548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.334208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.112660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:45.853312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:48.654204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:50.669152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.249028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:54.076271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.840533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.274196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:39.506461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:40.969821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.452732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.245824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:46.091637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:48.803655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:50.881514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.357846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:54.271448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:35.941957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:37.410000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:39.654957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:41.076801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:42.572254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:44.362736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:46.356544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:48.973443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:51.120377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T19:21:52.460341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-05-06T19:22:01.415044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
antiguedad_clienteantiguedad_empleadoduracion_creditoedadestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOestado_creditofalta_pago_Nfalta_pago_Ygastos_ult_12mgenero_Fgenero_Mimporte_solicitadoingresoslimite_credito_tcnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDoperaciones_ult_12mpct_ingresopersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAtasa_interes
antiguedad_cliente1.000-0.0010.000-0.0010.0490.0360.0400.0510.0320.0320.0260.0500.050-0.0240.0190.0190.0380.0130.0090.0000.0220.0290.0000.0240.0120.0000.0000.0130.0320.0170.000-0.0360.034-0.1150.0310.0340.0000.0000.009
antiguedad_empleado-0.0011.0000.0000.1090.0110.0000.0000.0110.0250.0250.0970.0400.0400.0640.0000.0000.1200.188-0.0040.0000.0000.0000.0000.0310.0210.0560.0170.1010.0210.0190.0000.058-0.003-0.0020.2080.2040.0190.034-0.065
duracion_credito0.0000.0001.0000.0050.0000.0000.0140.0000.0050.0050.0000.0000.0000.0000.0000.0000.0000.0000.0070.0080.0160.0000.0000.0320.0250.0000.0040.0090.0120.0220.0220.0000.0000.0160.0060.0110.0000.0000.017
edad-0.0010.1090.0051.0000.0170.0000.0140.0080.0160.0160.0400.0000.0000.0090.0000.0000.0780.1560.0110.0000.0000.0140.0000.0000.0000.1600.0120.2040.0050.0120.0380.007-0.0370.0010.0000.0240.0230.0250.005
estado_civil_CASADO0.0490.0110.0000.0171.0000.2600.2620.7410.0240.0240.0420.0000.0000.1740.0000.0000.0900.0210.0640.0040.0000.0000.0000.0130.0140.0200.0140.0100.0000.0000.0000.1710.0640.0220.0160.0130.0080.0000.000
estado_civil_DESCONOCIDO0.0360.0000.0000.0000.2601.0000.0780.2250.0000.0000.0190.0000.0000.0550.0110.0110.0420.0330.0170.0000.0000.0070.0000.0000.0000.0060.0000.0000.0000.0000.0000.0300.0000.0390.0130.0040.0000.0000.011
estado_civil_DIVORCIADO0.0400.0000.0140.0140.2620.0781.0000.2270.0000.0000.0000.0000.0000.0380.0000.0000.0000.0000.0210.0160.0000.0000.0090.0000.0340.0000.0190.0000.0000.0000.0000.0390.0030.0300.0000.0000.0000.0000.026
estado_civil_SOLTERO0.0510.0110.0000.0080.7410.2250.2271.0000.0170.0170.0310.0000.0000.1410.0130.0130.0670.0030.0330.0200.0000.0000.0000.0040.0000.0070.0000.0150.0000.0000.0070.1410.0410.0380.0210.0170.0000.0000.000
estado_cliente_ACTIVO0.0320.0250.0050.0160.0240.0000.0000.0171.0001.0000.1170.5510.5510.3290.0310.0310.1070.0180.0340.0070.0310.0000.0060.0000.0000.0150.0000.0210.0000.0000.0000.4580.0430.0190.0520.0540.0000.0000.319
estado_cliente_PASIVO0.0320.0250.0050.0160.0240.0000.0000.0171.0001.0000.1170.5510.5510.3290.0310.0310.1070.0180.0340.0070.0310.0000.0060.0000.0000.0150.0000.0210.0000.0000.0000.4580.0430.0190.0520.0540.0000.0000.319
estado_credito0.0260.0970.0000.0400.0420.0190.0000.0310.1170.1171.0000.1910.1910.2320.0260.0260.2100.1170.0000.0000.0040.0100.0070.0000.0000.0970.0630.1120.0620.0140.0420.2400.4050.0000.2070.1650.0230.1010.383
falta_pago_N0.0500.0400.0000.0000.0000.0000.0000.0000.5510.5510.1911.0001.0000.2610.0000.0000.0550.0000.0290.0000.0000.0000.0070.0060.0000.0140.0170.0490.0030.0000.0000.3240.0340.0160.0720.0740.0120.0000.561
falta_pago_Y0.0500.0400.0000.0000.0000.0000.0000.0000.5510.5510.1911.0001.0000.2610.0000.0000.0550.0000.0290.0000.0000.0000.0070.0060.0000.0140.0170.0490.0030.0000.0000.3240.0340.0160.0720.0740.0120.0000.561
gastos_ult_12m-0.0240.0640.0000.0090.1740.0550.0380.1410.3290.3290.2320.2610.2611.0000.2470.2470.0350.1570.0280.0210.0130.0000.0430.0000.0000.0130.0120.0000.0000.0000.0000.879-0.0710.0590.1520.1810.0000.037-0.187
genero_F0.0190.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1700.1130.4420.0000.0080.0000.0130.0000.0000.0090.0000.0000.0000.0000.0070.1680.0670.0000.0400.0410.0000.0000.004
genero_M0.0190.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1700.1130.4420.0000.0080.0000.0130.0000.0000.0090.0000.0000.0000.0000.0070.1680.0670.0000.0400.0410.0000.0000.004
importe_solicitado0.0380.1200.0000.0780.0900.0420.0000.0670.1070.1070.2100.0550.0550.0350.1700.1701.0000.3500.0390.0280.0100.0000.0000.0200.0000.0000.0170.0330.0000.0000.0460.0020.7400.0310.1900.1690.0120.0560.073
ingresos0.0130.1880.0000.1560.0210.0330.0000.0030.0180.0180.1170.0000.0000.1570.1130.1130.3501.0000.0380.0150.0000.0000.0230.0000.0140.0000.0180.0580.0440.0200.0340.129-0.2920.0200.1560.1200.0000.086-0.027
limite_credito_tc0.009-0.0040.0070.0110.0640.0170.0210.0330.0340.0340.0000.0290.0290.0280.4420.4420.0390.0381.0000.0000.0000.0000.0000.0000.0170.0210.0000.0000.0000.0050.0000.0300.0200.0490.0000.0230.0000.0100.003
nivel_educativo_DESCONOCIDO0.0000.0000.0080.0000.0040.0000.0160.0200.0070.0070.0000.0000.0000.0210.0000.0000.0280.0150.0001.0000.0910.0960.2070.2780.2380.0000.0000.0230.0190.0000.0000.0000.0000.0290.0100.0000.0000.0140.000
nivel_educativo_POSGRADO_COMPLETO0.0220.0000.0160.0000.0000.0000.0000.0000.0310.0310.0040.0000.0000.0130.0080.0080.0100.0000.0000.0911.0000.0490.1090.1460.1250.0000.0000.0180.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.009
nivel_educativo_POSGRADO_INCOMPLETO0.0290.0000.0000.0140.0000.0070.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0960.0491.0000.1150.1550.1330.0000.0170.0040.0000.0060.0000.0000.0140.0130.0000.0000.0000.0040.000
nivel_educativo_SECUNDARIO_COMPLETO0.0000.0000.0000.0000.0000.0000.0090.0000.0060.0060.0070.0070.0070.0430.0130.0130.0000.0230.0000.2070.1090.1151.0000.3320.2840.0030.0000.0000.0000.0000.0170.0000.0110.0110.0070.0000.0000.0000.009
nivel_educativo_UNIVERSITARIO_COMPLETO0.0240.0310.0320.0000.0130.0000.0000.0040.0000.0000.0000.0060.0060.0000.0000.0000.0200.0000.0000.2780.1460.1550.3321.0000.3820.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0120.000
nivel_educativo_UNIVERSITARIO_INCOMPLETO0.0120.0210.0250.0000.0140.0000.0340.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0170.2380.1250.1330.2840.3821.0000.0150.0000.0060.0000.0000.0070.0000.0000.0150.0040.0040.0000.0000.000
objetivo_credito_EDUCACIÓN0.0000.0560.0000.1600.0200.0060.0000.0070.0150.0150.0970.0140.0140.0130.0090.0090.0000.0000.0210.0000.0000.0000.0030.0000.0151.0000.2490.1680.2440.2430.2590.0000.0030.0000.0000.0000.0000.0000.037
objetivo_credito_INVERSIONES0.0000.0170.0040.0120.0140.0000.0190.0000.0000.0000.0630.0170.0170.0120.0000.0000.0170.0180.0000.0000.0000.0170.0000.0000.0000.2491.0000.1390.2010.2000.2130.0000.0100.0000.0450.0000.0000.0920.030
objetivo_credito_MEJORAS_HOGAR0.0130.1010.0090.2040.0100.0000.0000.0150.0210.0210.1120.0490.0490.0000.0000.0000.0330.0580.0000.0230.0180.0040.0000.0000.0060.1680.1391.0000.1360.1350.1440.0190.0290.0230.0340.0270.0000.0080.047
objetivo_credito_PAGO_DEUDAS0.0320.0210.0120.0050.0000.0000.0000.0000.0000.0000.0620.0030.0030.0000.0000.0000.0000.0440.0000.0190.0000.0000.0000.0000.0000.2440.2010.1361.0000.1960.2090.0110.0000.0130.0430.0000.0000.0920.015
objetivo_credito_PERSONAL0.0170.0190.0220.0120.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0200.0050.0000.0000.0060.0000.0000.0000.2430.2000.1350.1961.0000.2080.0270.0180.0360.0160.0200.0000.0000.017
objetivo_credito_SALUD0.0000.0000.0220.0380.0000.0000.0000.0070.0000.0000.0420.0000.0000.0000.0070.0070.0460.0340.0000.0000.0000.0000.0170.0000.0070.2590.2130.1440.2090.2081.0000.0000.0000.0000.0400.0390.0000.0000.026
operaciones_ult_12m-0.0360.0580.0000.0070.1710.0300.0390.1410.4580.4580.2400.3240.3240.8790.1680.1680.0020.1290.0300.0000.0360.0000.0000.0000.0000.0000.0000.0190.0110.0270.0001.000-0.0820.0560.1370.1650.0000.037-0.219
pct_ingreso0.034-0.0030.000-0.0370.0640.0000.0030.0410.0430.0430.4050.0340.034-0.0710.0670.0670.740-0.2920.0200.0000.0000.0140.0110.0000.0000.0030.0100.0290.0000.0180.000-0.0821.0000.0220.0600.0420.0290.0500.091
personas_a_cargo-0.115-0.0020.0160.0010.0220.0390.0300.0380.0190.0190.0000.0160.0160.0590.0000.0000.0310.0200.0490.0290.0000.0130.0110.0000.0150.0000.0000.0230.0130.0360.0000.0560.0221.0000.0000.0000.0000.014-0.011
situacion_vivienda_ALQUILER0.0310.2080.0060.0000.0160.0130.0000.0210.0520.0520.2070.0720.0720.1520.0400.0400.1900.1560.0000.0100.0000.0000.0070.0050.0040.0000.0450.0340.0430.0160.0400.1370.0600.0001.0000.8520.0760.3410.143
situacion_vivienda_HIPOTECA0.0340.2040.0110.0240.0130.0040.0000.0170.0540.0540.1650.0740.0740.1810.0410.0410.1690.1200.0230.0000.0000.0000.0000.0000.0040.0000.0000.0270.0000.0200.0390.1650.0420.0000.8521.0000.0390.1840.148
situacion_vivienda_OTROS0.0000.0190.0000.0230.0080.0000.0000.0000.0000.0000.0230.0120.0120.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0000.0760.0391.0000.0080.028
situacion_vivienda_PROPIA0.0000.0340.0000.0250.0000.0000.0000.0000.0000.0000.1010.0000.0000.0370.0000.0000.0560.0860.0100.0140.0000.0040.0000.0120.0000.0000.0920.0080.0920.0000.0000.0370.0500.0140.3410.1840.0081.0000.000
tasa_interes0.009-0.0650.0170.0050.0000.0110.0260.0000.3190.3190.3830.5610.561-0.1870.0040.0040.073-0.0270.0030.0000.0090.0000.0090.0000.0000.0370.0300.0470.0150.0170.026-0.2190.091-0.0110.1430.1480.0280.0001.000

Missing values

2025-05-06T19:21:54.568597image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-06T19:21:55.084911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETO
021100025.096000.1011.14039.01144.012691.042.03.0FalseFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
1233500024.0655000.5315.23136.01887.03418.020.03.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
2243500048.0544000.5514.27154.01314.09095.026.01.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
321250022.099000.257.14134.01171.03313.020.04.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalse
4263500038.0771000.4512.42121.0816.04716.028.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
5243500045.0789560.4411.11146.01330.034516.031.04.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
6243500028.0830000.428.90127.01538.029081.036.00.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
721160036.0100000.1614.74136.01350.022352.024.03.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
8223500046.0850000.4110.37136.01441.011656.032.02.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
921450022.0100000.458.63131.01201.06748.042.05.0FalseFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETO
1009122900034.0650000.149.63034.015577.013940.0114.01.0FalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
1009225950024.0610000.167.51050.014596.03688.0120.01.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalse
1009325950032.0680000.147.14040.015476.04003.0117.02.0TrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
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